python /home/admin/mtr/script_for_cron.py -j python_test3 -m 12 -a ' --short_python3 -v ' -s python_test3 -M 0 -S 0 -U 100,100,120 import MySQLdb succeeded Import error (python version) python version = 3 warning , we can't find thcl infos in json_data warning , we can't find pdt infos in json_data list_job_run_as_list : ['mask_detection', 'datou', 'CacheModelData_queries', 'CachePhotoData_queries', 'test_fork', 'prepare_maskdata', 'portfolio_queries', 'sla_mensuel'] python version used : 3 liste_fichiers : [('tests/mask_test', True, 'Test mask-detection ', 'mask_detection'), ('tests/datou_test', True, 'Datou All Test', 'datou', 'all'), ('mtr/database_queries/CacheModelData_queries', True, 'Test Cache Model Data', 'CacheModelData_queries'), ('tests/cache_photo_data_test', True, 'Test local_cache_photo ', 'CachePhotoData_queries'), ('mtr/mask_rcnn/prepare_maskdata', True, 'test prepare mask data', 'prepare_maskdata', 'all'), ('mtr/database_queries/portfolio_queries', True, 'test portfolio queries', 'portfolio_queries'), ('prod/memo/memo', True, 'SLA Mensuel', 'sla_mensuel', 'all')] #&_# BEGIN OF TEST : tests/mask_test #&_# /home/admin/workarea/git/Velours/python/tests/mask_test.py Test mask-detection python version used : 3 ############################### TEST memory used ################################ free memory at begining : begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 376 run mask_detect Inside batchDatouExec : verbose : False # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : mask_detect list_input_json : [] origin BFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 time to download the photos : 0.11449980735778809 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:mask_detect Tue Jul 15 06:35:28 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Beginning of datou step mask_detect ! save_polygon : True begin detect begin to check gpu status inside check gpu memory havn't enough memory gpu , need / 3000 l 3632 free memory gpu now : 376 wait 20 seconds l 3637 free memory gpu now : 376 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 /home/admin/workarea/git/Velours/python/tests/python_tests.py:11: DeprecationWarning: the imp module is deprecated in favour of importlib; see the module's documentation for alternative uses import imp 2025-07-15 06:35:50.533010: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-07-15 06:35:50.559448: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493035000 Hz 2025-07-15 06:35:50.561415: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f7d0c000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-07-15 06:35:50.561475: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-07-15 06:35:50.564943: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-07-15 06:35:50.698720: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x3b226f70 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-07-15 06:35:50.698765: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-07-15 06:35:50.699635: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-07-15 06:35:50.700009: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-07-15 06:35:50.702857: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-07-15 06:35:50.705267: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-07-15 06:35:50.705680: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-07-15 06:35:50.708113: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-07-15 06:35:50.709464: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-07-15 06:35:50.713813: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-07-15 06:35:50.714633: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-07-15 06:35:50.714704: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-07-15 06:35:50.715136: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-07-15 06:35:50.715150: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-07-15 06:35:50.715174: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-07-15 06:35:50.715944: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 0 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) WARNING:tensorflow:From /home/admin/workarea/git/Velours/python/mtr/mask_rcnn/mask_detection.py:69: The name tf.keras.backend.set_session is deprecated. Please use tf.compat.v1.keras.backend.set_session instead. Inside mask_sub_process Inside mask_detect About to load cache.load_thcl_param To do loadFromThcl(), then load ParamDescType : thcl454 thcls : [{'id': 454, 'mtr_user_id': 31, 'name': 'mask_coco_origin', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'backgroud,person,bicycle,car,motorcycle,airplane,bus,train,truck,boat,trafficlight,firehydrant,stopsign,parkingmeter,bench,bird,cat,dog,horse,sheep,cow,elephant,bear,zebra,giraffe,backpack,umbrella,handbag,tie,suitcase,frisbee,skis,snowboard,sportsball,kite,baseballbat,baseballglove,skateboard,surfboard,tennisracket,bottle,wineglass,cup,fork,knife,spoon,bowl,banana,apple,sandwich,orange,broccoli,carrot,hotdog,pizza,donut,cake,chair,couch,pottedplant,bed,diningtable,toilet,tv,laptop,mouse,remote,keyboard,cellphone,microwave,oven,toaster,sink,refrigerator,book,clock,vase,scissors,teddybear,hairdrier,toothbrush', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 445, 'photo_desc_type': 3473, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0'}] thcl {'id': 454, 'mtr_user_id': 31, 'name': 'mask_coco_origin', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'backgroud,person,bicycle,car,motorcycle,airplane,bus,train,truck,boat,trafficlight,firehydrant,stopsign,parkingmeter,bench,bird,cat,dog,horse,sheep,cow,elephant,bear,zebra,giraffe,backpack,umbrella,handbag,tie,suitcase,frisbee,skis,snowboard,sportsball,kite,baseballbat,baseballglove,skateboard,surfboard,tennisracket,bottle,wineglass,cup,fork,knife,spoon,bowl,banana,apple,sandwich,orange,broccoli,carrot,hotdog,pizza,donut,cake,chair,couch,pottedplant,bed,diningtable,toilet,tv,laptop,mouse,remote,keyboard,cellphone,microwave,oven,toaster,sink,refrigerator,book,clock,vase,scissors,teddybear,hairdrier,toothbrush', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 445, 'photo_desc_type': 3473, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0'} Update svm_hashtag_type_desc : 3473 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (3473, 'mask_coco_origin', 16384, 25088, 'mask_coco_origin', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 1, datetime.datetime(2018, 3, 19, 10, 42, 21), datetime.datetime(2018, 3, 19, 10, 42, 21)) {'thcl': {'id': 454, 'mtr_user_id': 31, 'name': 'mask_coco_origin', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'backgroud,person,bicycle,car,motorcycle,airplane,bus,train,truck,boat,trafficlight,firehydrant,stopsign,parkingmeter,bench,bird,cat,dog,horse,sheep,cow,elephant,bear,zebra,giraffe,backpack,umbrella,handbag,tie,suitcase,frisbee,skis,snowboard,sportsball,kite,baseballbat,baseballglove,skateboard,surfboard,tennisracket,bottle,wineglass,cup,fork,knife,spoon,bowl,banana,apple,sandwich,orange,broccoli,carrot,hotdog,pizza,donut,cake,chair,couch,pottedplant,bed,diningtable,toilet,tv,laptop,mouse,remote,keyboard,cellphone,microwave,oven,toaster,sink,refrigerator,book,clock,vase,scissors,teddybear,hairdrier,toothbrush', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 445, 'photo_desc_type': 3473, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0'}, 'list_hashtags': ['backgroud', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sportsball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush'], 'list_hashtags_csv': 'backgroud,person,bicycle,car,motorcycle,airplane,bus,train,truck,boat,trafficlight,firehydrant,stopsign,parkingmeter,bench,bird,cat,dog,horse,sheep,cow,elephant,bear,zebra,giraffe,backpack,umbrella,handbag,tie,suitcase,frisbee,skis,snowboard,sportsball,kite,baseballbat,baseballglove,skateboard,surfboard,tennisracket,bottle,wineglass,cup,fork,knife,spoon,bowl,banana,apple,sandwich,orange,broccoli,carrot,hotdog,pizza,donut,cake,chair,couch,pottedplant,bed,diningtable,toilet,tv,laptop,mouse,remote,keyboard,cellphone,microwave,oven,toaster,sink,refrigerator,book,clock,vase,scissors,teddybear,hairdrier,toothbrush', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 445, 'svm_hashtag_type_desc': 3473, 'photo_desc_type': 3473, 'pb_hashtag_id_or_classifier': 0} list_class_names : ['backgroud', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sportsball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush'] Configurations: BACKBONE resnet101 BACKBONE_SHAPES [[160 160] [ 80 80] [ 40 40] [ 20 20] [ 10 10]] BACKBONE_STRIDES [4, 8, 16, 32, 64] BATCH_SIZE 1 BBOX_STD_DEV [0.1 0.1 0.2 0.2] DETECTION_MAX_INSTANCES 100 DETECTION_MIN_CONFIDENCE 0.3 DETECTION_NMS_THRESHOLD 0.3 GPU_COUNT 1 IMAGES_PER_GPU 1 IMAGE_MAX_DIM 640 IMAGE_MIN_DIM 640 IMAGE_PADDING True IMAGE_SHAPE [640 640 3] LEARNING_MOMENTUM 0.9 LEARNING_RATE 0.001 LOSS_WEIGHTS {'rpn_class_loss': 1.0, 'rpn_bbox_loss': 1.0, 'mrcnn_class_loss': 1.0, 'mrcnn_bbox_loss': 1.0, 'mrcnn_mask_loss': 1.0} MASK_POOL_SIZE 14 MASK_SHAPE [28, 28] MAX_GT_INSTANCES 100 MEAN_PIXEL [123.7 116.8 103.9] MINI_MASK_SHAPE (56, 56) NAME mask_coco_origin NUM_CLASSES 81 POOL_SIZE 7 POST_NMS_ROIS_INFERENCE 1000 POST_NMS_ROIS_TRAINING 2000 ROI_POSITIVE_RATIO 0.33 RPN_ANCHOR_RATIOS [0.5, 1, 2] RPN_ANCHOR_SCALES (16, 32, 64, 128, 256) RPN_ANCHOR_STRIDE 1 2025-07-15 06:35:51.252374: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-07-15 06:35:51.252461: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-07-15 06:35:51.252489: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-07-15 06:35:51.252515: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-07-15 06:35:51.252540: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-07-15 06:35:51.252564: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-07-15 06:35:51.252602: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-07-15 06:35:51.252628: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-07-15 06:35:51.253637: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-07-15 06:35:51.254726: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-07-15 06:35:51.254771: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-07-15 06:35:51.254797: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-07-15 06:35:51.254821: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-07-15 06:35:51.254844: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-07-15 06:35:51.254868: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-07-15 06:35:51.254891: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-07-15 06:35:51.254915: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-07-15 06:35:51.255955: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-07-15 06:35:51.255996: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-07-15 06:35:51.256010: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-07-15 06:35:51.256022: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-07-15 06:35:51.256818: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 0 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) 2025-07-15 06:36:01.646734: W tensorflow/core/common_runtime/bfc_allocator.cc:434] Allocator (GPU_0_bfc) ran out of memory trying to allocate 144.0KiB (rounded to 147456) Current allocation summary follows. 2025-07-15 06:36:01.646779: I tensorflow/core/common_runtime/bfc_allocator.cc:934] BFCAllocator dump for GPU_0_bfc 2025-07-15 06:36:01.646792: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (256): Total Chunks: 16, Chunks in use: 16. 4.0KiB allocated for chunks. 4.0KiB in use in bin. 2.5KiB client-requested in use in bin. 2025-07-15 06:36:01.646803: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (512): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-15 06:36:01.646814: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (1024): Total Chunks: 1, Chunks in use: 1. 1.2KiB allocated for chunks. 1.2KiB in use in bin. 1.0KiB client-requested in use in bin. 2025-07-15 06:36:01.646824: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (2048): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-15 06:36:01.646834: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (4096): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-15 06:36:01.646844: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (8192): Total Chunks: 1, Chunks in use: 0. 14.8KiB allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-15 06:36:01.646874: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (16384): Total Chunks: 3, Chunks in use: 1. 55.5KiB allocated for chunks. 16.0KiB in use in bin. 16.0KiB client-requested in use in bin. 2025-07-15 06:36:01.646885: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (32768): Total Chunks: 1, Chunks in use: 1. 52.5KiB allocated for chunks. 52.5KiB in use in bin. 36.8KiB client-requested in use in bin. 2025-07-15 06:36:01.646895: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (65536): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-15 06:36:01.646904: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (131072): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-15 06:36:01.646914: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (262144): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-15 06:36:01.646923: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (524288): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-15 06:36:01.646932: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (1048576): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-15 06:36:01.646942: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (2097152): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-15 06:36:01.646951: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (4194304): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-15 06:36:01.646960: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (8388608): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-15 06:36:01.646970: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (16777216): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-15 06:36:01.646979: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (33554432): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-15 06:36:01.646988: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (67108864): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-15 06:36:01.646998: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (134217728): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-15 06:36:01.647007: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (268435456): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-15 06:36:01.647017: I tensorflow/core/common_runtime/bfc_allocator.cc:957] Bin for 144.0KiB was 128.0KiB, Chunk State: 2025-07-15 06:36:01.647026: I tensorflow/core/common_runtime/bfc_allocator.cc:970] Next region of size 131072 2025-07-15 06:36:01.647039: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce00000 of size 1280 next 1 2025-07-15 06:36:01.647048: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce00500 of size 256 next 5 2025-07-15 06:36:01.647056: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce00600 of size 256 next 7 2025-07-15 06:36:01.647065: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce00700 of size 256 next 8 2025-07-15 06:36:01.647073: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce00800 of size 256 next 9 2025-07-15 06:36:01.647088: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce00900 of size 256 next 10 2025-07-15 06:36:01.647097: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce00a00 of size 256 next 11 2025-07-15 06:36:01.647105: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce00b00 of size 256 next 12 2025-07-15 06:36:01.647113: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce00c00 of size 256 next 16 2025-07-15 06:36:01.647122: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce00d00 of size 256 next 18 2025-07-15 06:36:01.647130: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce00e00 of size 256 next 19 2025-07-15 06:36:01.647138: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce00f00 of size 256 next 20 2025-07-15 06:36:01.647147: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce01000 of size 256 next 21 2025-07-15 06:36:01.647155: I tensorflow/core/common_runtime/bfc_allocator.cc:990] Free at 7f7c6ce01100 of size 15104 next 13 2025-07-15 06:36:01.647181: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce04c00 of size 256 next 14 2025-07-15 06:36:01.647192: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce04d00 of size 256 next 15 2025-07-15 06:36:01.647203: I tensorflow/core/common_runtime/bfc_allocator.cc:990] Free at 7f7c6ce04e00 of size 18944 next 2 2025-07-15 06:36:01.647214: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce09800 of size 256 next 3 2025-07-15 06:36:01.647225: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce09900 of size 256 next 4 2025-07-15 06:36:01.647236: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce09a00 of size 16384 next 17 2025-07-15 06:36:01.647248: I tensorflow/core/common_runtime/bfc_allocator.cc:990] Free at 7f7c6ce0da00 of size 21504 next 6 2025-07-15 06:36:01.647257: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce12e00 of size 53760 next 18446744073709551615 2025-07-15 06:36:01.647265: I tensorflow/core/common_runtime/bfc_allocator.cc:995] Summary of in-use Chunks by size: 2025-07-15 06:36:01.647276: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 16 Chunks of size 256 totalling 4.0KiB 2025-07-15 06:36:01.647285: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 1280 totalling 1.2KiB 2025-07-15 06:36:01.647295: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 16384 totalling 16.0KiB 2025-07-15 06:36:01.647304: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 53760 totalling 52.5KiB 2025-07-15 06:36:01.647313: I tensorflow/core/common_runtime/bfc_allocator.cc:1002] Sum Total of in-use chunks: 73.8KiB 2025-07-15 06:36:01.647322: I tensorflow/core/common_runtime/bfc_allocator.cc:1004] total_region_allocated_bytes_: 131072 memory_limit_: 131072 available bytes: 0 curr_region_allocation_bytes_: 262144 2025-07-15 06:36:01.647333: I tensorflow/core/common_runtime/bfc_allocator.cc:1010] Stats: Limit: 131072 InUse: 75520 MaxInUse: 130816 NumAllocs: 49 MaxAllocSize: 53760 2025-07-15 06:36:01.647344: W tensorflow/core/common_runtime/bfc_allocator.cc:439] ****__________**_____________**************_______________******************************xxxxxxxxxxxx 2025-07-15 06:36:01.647379: W tensorflow/core/framework/op_kernel.cc:1753] OP_REQUIRES failed at random_op.cc:77 : Resource exhausted: OOM when allocating tensor with shape[3,3,64,64] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc RPN_BBOX_STD_DEV [0.1 0.1 0.2 0.2] RPN_NMS_THRESHOLD 0.7 RPN_TRAIN_ANCHORS_PER_IMAGE 256 STEPS_PER_EPOCH 1000 TRAIN_ROIS_PER_IMAGE 200 USE_MINI_MASK True USE_RPN_ROIS True VALIDATION_STEPS 50 WEIGHT_DECAY 0.0001 Exception in mask_detect : OOM when allocating tensor with shape[3,3,64,64] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc [Op:RandomUniform] we want to redo the detection Using TensorFlow backend. max_time_sub_proc : 3600 erreur pendant la detection Useless call to update_current_state in case -12 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : False eke 12-6-18 : saveMask need to be cleaned for new output ! ERROR : mask output needs to be a dictionnary now ! No output to save, continue without doing anything ! save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : -12 free memory after detection : begin to check gpu status inside check gpu memory l 3610 free memory gpu now : 87 ############################### TEST detect object ################################ run mask_detect Inside batchDatouExec : verbose : False Catched exception ! Connect or reconnect ! # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! List Step Type Loaded in datou : mask_detect list_input_json : [] origin BFwe have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 time to download the photos : 0.12265944480895996 About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : False number of steps : 1 step1:mask_detect Tue Jul 15 06:36:02 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec Beginning of datou step mask_detect ! save_polygon : True begin detect begin to check gpu status inside check gpu memory havn't enough memory gpu , need / 3000 l 3632 free memory gpu now : 87 wait 20 seconds l 3637 free memory gpu now : 87 max_wait_temp : 1 max_wait : 0 gpu_flag : 0 2025-07-15 06:36:25.812281: I tensorflow/core/platform/cpu_feature_guard.cc:143] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 2025-07-15 06:36:25.843520: I tensorflow/core/platform/profile_utils/cpu_utils.cc:102] CPU Frequency: 3493035000 Hz 2025-07-15 06:36:25.849511: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x7f7d0c000b60 initialized for platform Host (this does not guarantee that XLA will be used). Devices: 2025-07-15 06:36:25.849737: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version 2025-07-15 06:36:25.854951: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcuda.so.1 2025-07-15 06:36:26.018650: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x3b105380 initialized for platform CUDA (this does not guarantee that XLA will be used). Devices: 2025-07-15 06:36:26.018722: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): NVIDIA GeForce RTX 2080 Ti, Compute Capability 7.5 2025-07-15 06:36:26.019715: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-07-15 06:36:26.020195: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-07-15 06:36:26.022797: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-07-15 06:36:26.025573: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-07-15 06:36:26.026222: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-07-15 06:36:26.029043: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-07-15 06:36:26.030785: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-07-15 06:36:26.036908: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-07-15 06:36:26.038209: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-07-15 06:36:26.038389: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-07-15 06:36:26.039097: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-07-15 06:36:26.039135: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-07-15 06:36:26.039151: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-07-15 06:36:26.040401: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 0 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) WARNING:tensorflow:From /home/admin/workarea/git/Velours/python/mtr/mask_rcnn/mask_detection.py:69: The name tf.keras.backend.set_session is deprecated. Please use tf.compat.v1.keras.backend.set_session instead. Inside mask_sub_process Inside mask_detect About to load cache.load_thcl_param To do loadFromThcl(), then load ParamDescType : thcl454 thcls : [{'id': 454, 'mtr_user_id': 31, 'name': 'mask_coco_origin', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'backgroud,person,bicycle,car,motorcycle,airplane,bus,train,truck,boat,trafficlight,firehydrant,stopsign,parkingmeter,bench,bird,cat,dog,horse,sheep,cow,elephant,bear,zebra,giraffe,backpack,umbrella,handbag,tie,suitcase,frisbee,skis,snowboard,sportsball,kite,baseballbat,baseballglove,skateboard,surfboard,tennisracket,bottle,wineglass,cup,fork,knife,spoon,bowl,banana,apple,sandwich,orange,broccoli,carrot,hotdog,pizza,donut,cake,chair,couch,pottedplant,bed,diningtable,toilet,tv,laptop,mouse,remote,keyboard,cellphone,microwave,oven,toaster,sink,refrigerator,book,clock,vase,scissors,teddybear,hairdrier,toothbrush', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 445, 'photo_desc_type': 3473, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0'}] thcl {'id': 454, 'mtr_user_id': 31, 'name': 'mask_coco_origin', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'backgroud,person,bicycle,car,motorcycle,airplane,bus,train,truck,boat,trafficlight,firehydrant,stopsign,parkingmeter,bench,bird,cat,dog,horse,sheep,cow,elephant,bear,zebra,giraffe,backpack,umbrella,handbag,tie,suitcase,frisbee,skis,snowboard,sportsball,kite,baseballbat,baseballglove,skateboard,surfboard,tennisracket,bottle,wineglass,cup,fork,knife,spoon,bowl,banana,apple,sandwich,orange,broccoli,carrot,hotdog,pizza,donut,cake,chair,couch,pottedplant,bed,diningtable,toilet,tv,laptop,mouse,remote,keyboard,cellphone,microwave,oven,toaster,sink,refrigerator,book,clock,vase,scissors,teddybear,hairdrier,toothbrush', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 445, 'photo_desc_type': 3473, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0'} Update svm_hashtag_type_desc : 3473 FOUND : 1 Here is data_from_sql_as_vec to set the ParamDescriptorType : (3473, 'mask_coco_origin', 16384, 25088, 'mask_coco_origin', 'pool5', 10.0, None, None, 256, None, 0, None, 8, None, None, -1000.0, 1, datetime.datetime(2018, 3, 19, 10, 42, 21), datetime.datetime(2018, 3, 19, 10, 42, 21)) {'thcl': {'id': 454, 'mtr_user_id': 31, 'name': 'mask_coco_origin', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'backgroud,person,bicycle,car,motorcycle,airplane,bus,train,truck,boat,trafficlight,firehydrant,stopsign,parkingmeter,bench,bird,cat,dog,horse,sheep,cow,elephant,bear,zebra,giraffe,backpack,umbrella,handbag,tie,suitcase,frisbee,skis,snowboard,sportsball,kite,baseballbat,baseballglove,skateboard,surfboard,tennisracket,bottle,wineglass,cup,fork,knife,spoon,bowl,banana,apple,sandwich,orange,broccoli,carrot,hotdog,pizza,donut,cake,chair,couch,pottedplant,bed,diningtable,toilet,tv,laptop,mouse,remote,keyboard,cellphone,microwave,oven,toaster,sink,refrigerator,book,clock,vase,scissors,teddybear,hairdrier,toothbrush', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 445, 'photo_desc_type': 3473, 'type_classification': 'mask_rcnn', 'hashtag_id_list': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0'}, 'list_hashtags': ['backgroud', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sportsball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush'], 'list_hashtags_csv': 'backgroud,person,bicycle,car,motorcycle,airplane,bus,train,truck,boat,trafficlight,firehydrant,stopsign,parkingmeter,bench,bird,cat,dog,horse,sheep,cow,elephant,bear,zebra,giraffe,backpack,umbrella,handbag,tie,suitcase,frisbee,skis,snowboard,sportsball,kite,baseballbat,baseballglove,skateboard,surfboard,tennisracket,bottle,wineglass,cup,fork,knife,spoon,bowl,banana,apple,sandwich,orange,broccoli,carrot,hotdog,pizza,donut,cake,chair,couch,pottedplant,bed,diningtable,toilet,tv,laptop,mouse,remote,keyboard,cellphone,microwave,oven,toaster,sink,refrigerator,book,clock,vase,scissors,teddybear,hairdrier,toothbrush', 'svm_portfolios_learning': '0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0', 'photo_hashtag_type': 445, 'svm_hashtag_type_desc': 3473, 'photo_desc_type': 3473, 'pb_hashtag_id_or_classifier': 0} list_class_names : ['backgroud', 'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'trafficlight', 'firehydrant', 'stopsign', 'parkingmeter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard', 'sportsball', 'kite', 'baseballbat', 'baseballglove', 'skateboard', 'surfboard', 'tennisracket', 'bottle', 'wineglass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange', 'broccoli', 'carrot', 'hotdog', 'pizza', 'donut', 'cake', 'chair', 'couch', 'pottedplant', 'bed', 'diningtable', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cellphone', 'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddybear', 'hairdrier', 'toothbrush'] Configurations: BACKBONE resnet101 BACKBONE_SHAPES [[160 160] [ 80 80] [ 40 40] [ 20 20] [ 10 10]] BACKBONE_STRIDES [4, 8, 16, 32, 64] BATCH_SIZE 1 BBOX_STD_DEV [0.1 0.1 0.2 0.2] DETECTION_MAX_INSTANCES 100 DETECTION_MIN_CONFIDENCE 0.3 DETECTION_NMS_THRESHOLD 0.3 GPU_COUNT 1 IMAGES_PER_GPU 1 IMAGE_MAX_DIM 640 IMAGE_MIN_DIM 640 IMAGE_PADDING True IMAGE_SHAPE [640 640 3] LEARNING_MOMENTUM 0.9 LEARNING_RATE 0.001 LOSS_WEIGHTS {'rpn_class_loss': 1.0, 'rpn_bbox_loss': 1.0, 'mrcnn_class_loss': 1.0, 'mrcnn_bbox_loss': 1.0, 'mrcnn_mask_loss': 1.0} MASK_POOL_SIZE 14 MASK_SHAPE [28, 28] MAX_GT_INSTANCES 100 MEAN_PIXEL [123.7 116.8 103.9] MINI_MASK_SHAPE (56, 56) NAME mask_coco_origin NUM_CLASSES 81 POOL_SIZE 7 POST_NMS_ROIS_INFERENCE 1000 POST_NMS_ROIS_TRAINING 2000 ROI_POSITIVE_RATIO 0.33 RPN_ANCHOR_RATIOS [0.5, 1, 2] RPN_ANCHOR_SCALES (16, 32, 64, 128, 256) RPN_ANCHOR_STRIDE 1 2025-07-15 06:36:26.691143: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-07-15 06:36:26.691262: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-07-15 06:36:26.691281: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-07-15 06:36:26.691301: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-07-15 06:36:26.691319: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-07-15 06:36:26.691336: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-07-15 06:36:26.691352: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-07-15 06:36:26.691369: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-07-15 06:36:26.692046: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-07-15 06:36:26.693023: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1561] Found device 0 with properties: pciBusID: 0000:41:00.0 name: NVIDIA GeForce RTX 2080 Ti computeCapability: 7.5 coreClock: 1.545GHz coreCount: 68 deviceMemorySize: 10.76GiB deviceMemoryBandwidth: 573.69GiB/s 2025-07-15 06:36:26.693072: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1 2025-07-15 06:36:26.693088: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2025-07-15 06:36:26.693102: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcufft.so.10 2025-07-15 06:36:26.693117: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcurand.so.10 2025-07-15 06:36:26.693131: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusolver.so.10 2025-07-15 06:36:26.693145: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcusparse.so.10 2025-07-15 06:36:26.693159: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2025-07-15 06:36:26.693811: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1703] Adding visible gpu devices: 0 2025-07-15 06:36:26.693846: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1102] Device interconnect StreamExecutor with strength 1 edge matrix: 2025-07-15 06:36:26.693855: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1108] 0 2025-07-15 06:36:26.693863: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1121] 0: N 2025-07-15 06:36:26.694590: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1247] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 0 MB memory) -> physical GPU (device: 0, name: NVIDIA GeForce RTX 2080 Ti, pci bus id: 0000:41:00.0, compute capability: 7.5) 2025-07-15 06:36:37.174666: W tensorflow/core/common_runtime/bfc_allocator.cc:434] Allocator (GPU_0_bfc) ran out of memory trying to allocate 144.0KiB (rounded to 147456) Current allocation summary follows. 2025-07-15 06:36:37.174723: I tensorflow/core/common_runtime/bfc_allocator.cc:934] BFCAllocator dump for GPU_0_bfc 2025-07-15 06:36:37.174741: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (256): Total Chunks: 16, Chunks in use: 16. 4.0KiB allocated for chunks. 4.0KiB in use in bin. 2.5KiB client-requested in use in bin. 2025-07-15 06:36:37.174756: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (512): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-15 06:36:37.174771: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (1024): Total Chunks: 1, Chunks in use: 1. 1.2KiB allocated for chunks. 1.2KiB in use in bin. 1.0KiB client-requested in use in bin. 2025-07-15 06:36:37.174785: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (2048): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-15 06:36:37.174799: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (4096): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-15 06:36:37.174813: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (8192): Total Chunks: 1, Chunks in use: 0. 14.8KiB allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-15 06:36:37.174829: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (16384): Total Chunks: 3, Chunks in use: 1. 55.5KiB allocated for chunks. 16.0KiB in use in bin. 16.0KiB client-requested in use in bin. 2025-07-15 06:36:37.174844: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (32768): Total Chunks: 1, Chunks in use: 1. 52.5KiB allocated for chunks. 52.5KiB in use in bin. 36.8KiB client-requested in use in bin. 2025-07-15 06:36:37.174858: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (65536): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-15 06:36:37.174871: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (131072): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-15 06:36:37.174910: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (262144): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-15 06:36:37.174924: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (524288): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-15 06:36:37.174937: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (1048576): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-15 06:36:37.174950: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (2097152): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-15 06:36:37.174964: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (4194304): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-15 06:36:37.174977: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (8388608): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-15 06:36:37.174990: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (16777216): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-15 06:36:37.175003: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (33554432): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-15 06:36:37.175017: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (67108864): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-15 06:36:37.175030: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (134217728): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-15 06:36:37.175043: I tensorflow/core/common_runtime/bfc_allocator.cc:941] Bin (268435456): Total Chunks: 0, Chunks in use: 0. 0B allocated for chunks. 0B in use in bin. 0B client-requested in use in bin. 2025-07-15 06:36:37.175058: I tensorflow/core/common_runtime/bfc_allocator.cc:957] Bin for 144.0KiB was 128.0KiB, Chunk State: 2025-07-15 06:36:37.175069: I tensorflow/core/common_runtime/bfc_allocator.cc:970] Next region of size 131072 2025-07-15 06:36:37.175086: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce00000 of size 1280 next 1 2025-07-15 06:36:37.175099: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce00500 of size 256 next 5 2025-07-15 06:36:37.175111: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce00600 of size 256 next 7 2025-07-15 06:36:37.175123: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce00700 of size 256 next 8 2025-07-15 06:36:37.175135: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce00800 of size 256 next 9 2025-07-15 06:36:37.175146: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce00900 of size 256 next 10 2025-07-15 06:36:37.175178: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce00a00 of size 256 next 11 2025-07-15 06:36:37.175194: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce00b00 of size 256 next 12 2025-07-15 06:36:37.175206: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce00c00 of size 256 next 16 2025-07-15 06:36:37.175217: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce00d00 of size 256 next 18 2025-07-15 06:36:37.175229: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce00e00 of size 256 next 19 2025-07-15 06:36:37.175250: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce00f00 of size 256 next 20 2025-07-15 06:36:37.175263: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce01000 of size 256 next 21 2025-07-15 06:36:37.175275: I tensorflow/core/common_runtime/bfc_allocator.cc:990] Free at 7f7c6ce01100 of size 15104 next 13 2025-07-15 06:36:37.175286: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce04c00 of size 256 next 14 2025-07-15 06:36:37.175298: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce04d00 of size 256 next 15 2025-07-15 06:36:37.175310: I tensorflow/core/common_runtime/bfc_allocator.cc:990] Free at 7f7c6ce04e00 of size 18944 next 2 2025-07-15 06:36:37.175322: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce09800 of size 256 next 3 2025-07-15 06:36:37.175334: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce09900 of size 256 next 4 2025-07-15 06:36:37.175346: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce09a00 of size 16384 next 17 2025-07-15 06:36:37.175358: I tensorflow/core/common_runtime/bfc_allocator.cc:990] Free at 7f7c6ce0da00 of size 21504 next 6 2025-07-15 06:36:37.175370: I tensorflow/core/common_runtime/bfc_allocator.cc:990] InUse at 7f7c6ce12e00 of size 53760 next 18446744073709551615 2025-07-15 06:36:37.175382: I tensorflow/core/common_runtime/bfc_allocator.cc:995] Summary of in-use Chunks by size: 2025-07-15 06:36:37.175396: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 16 Chunks of size 256 totalling 4.0KiB 2025-07-15 06:36:37.175409: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 1280 totalling 1.2KiB 2025-07-15 06:36:37.175423: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 16384 totalling 16.0KiB 2025-07-15 06:36:37.175436: I tensorflow/core/common_runtime/bfc_allocator.cc:998] 1 Chunks of size 53760 totalling 52.5KiB 2025-07-15 06:36:37.175449: I tensorflow/core/common_runtime/bfc_allocator.cc:1002] Sum Total of in-use chunks: 73.8KiB 2025-07-15 06:36:37.175461: I tensorflow/core/common_runtime/bfc_allocator.cc:1004] total_region_allocated_bytes_: 131072 memory_limit_: 131072 available bytes: 0 curr_region_allocation_bytes_: 262144 2025-07-15 06:36:37.175477: I tensorflow/core/common_runtime/bfc_allocator.cc:1010] Stats: Limit: 131072 InUse: 75520 MaxInUse: 130816 NumAllocs: 49 MaxAllocSize: 53760 2025-07-15 06:36:37.175492: W tensorflow/core/common_runtime/bfc_allocator.cc:439] ****__________**_____________**************_______________******************************xxxxxxxxxxxx 2025-07-15 06:36:37.175534: W tensorflow/core/framework/op_kernel.cc:1753] OP_REQUIRES failed at random_op.cc:77 : Resource exhausted: OOM when allocating tensor with shape[3,3,64,64] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc RPN_BBOX_STD_DEV [0.1 0.1 0.2 0.2] RPN_NMS_THRESHOLD 0.7 RPN_TRAIN_ANCHORS_PER_IMAGE 256 STEPS_PER_EPOCH 1000 TRAIN_ROIS_PER_IMAGE 200 USE_MINI_MASK True USE_RPN_ROIS True VALIDATION_STEPS 50 WEIGHT_DECAY 0.0001 Exception in mask_detect : OOM when allocating tensor with shape[3,3,64,64] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc [Op:RandomUniform] we want to redo the detection Using TensorFlow backend. max_time_sub_proc : 3600 erreur pendant la detection Useless call to update_current_state in case -12 caffe_path_current : About to save ! 1 Inside saveOutput : final : True verbose : False eke 12-6-18 : saveMask need to be cleaned for new output ! ERROR : mask output needs to be a dictionnary now ! No output to save, continue without doing anything ! save missing photos in datou_result : After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : -12 ERROR : 'int' object is not subscriptable reconnect to base ! warning , we can't find thcl infos in json_data warning , we can't find pdt infos in json_data #&_# TEST FAILED #&_# : tests/mask_test #&_# Error : invalid literal for int() with base 10: "'int' object is not subscriptable" /home/admin/workarea/git/Velours/python/tests/python_tests.py refs/heads/master_361dc0ff97ce99e7df7f60b13951c603625c9707 SQL :INSERT INTO MTRAdmin.monitor_sys (name, type, server, version_code, result_str, result_bool, lien , test_group ,test_name) VALUES ('python_test3','1','marlene','refs/heads/master_361dc0ff97ce99e7df7f60b13951c603625c9707','{"mask_detection": "fail"}','0','http://marlene.fotonower-preprod.com/job/2025/July/15072025/python_test3//data_4/data_log/job/2025/July/15072025/python_test3/log-python3----short_python3--v--marlene-06:35:01.txt','mask_detection','unknown'); #&_# END OF TEST #&_# : tests/mask_test #&_# #&_# BEGIN OF TEST : tests/datou_test #&_# /home/admin/workarea/git/Velours/python/tests/datou_test.py Datou All Test python version used : 3 ############################### TEST sam ################################ TEST SAM Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=4573 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=4573 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 4573 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=4573 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : sam list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT photo_id, url FROM MTRBack.photos ph WHERE photo_id IN (1189321094) Found this number of photos: 1 ##### Call download_photos : nb_thread : 5 begin to download photo : 1189321094 download finish for photo 1189321094 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 ##### After load_data_input time to download the photos : 0.18155217170715332 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! WARNING : we have an input that is not a photo, we should get rid of it Calling datou_exec Inside datou_exec : verbose : True number of steps : 1 step1:sam Tue Jul 15 06:36:37 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1752554197_118993_1189321094_9626af7f95d010f2a4fd524688d4ea22_76896585.png': 1189321094} map_photo_id_path_extension : {1189321094: {'path': 'temp/1752554197_118993_1189321094_9626af7f95d010f2a4fd524688d4ea22_76896585.png', 'extension': 'png'}} map_subphoto_mainphoto : {} Beginning of datou step sam ! pht : 4677 Inside sam : nb paths : 1 ERROR in datou_step_exec, will save and exit ! CUDA error: out of memory CUDA kernel errors might be asynchronously reported at some other API call,so the stacktrace below might be incorrect. For debugging consider passing CUDA_LAUNCH_BLOCKING=1. File "/home/admin/workarea/git/Velours/python/mtr/datou/datou_lib.py", line 2329, in datou_exec output = datou_step_exec(sNext, args, cache, context, map_info, verbose, mtr_user_id) File "/home/admin/workarea/git/Velours/python/mtr/datou/datou_lib.py", line 2430, in datou_step_exec return lib_process.datou_step_sam(param, json_param, args, cache, context, map_info, verbose) File "/home/admin/workarea/git/Velours/python/mtr/datou/lib_step_exec/lib_step_process.py", line 367, in datou_step_sam sam.to(device=device) File "/home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 927, in to return self._apply(convert) File "/home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 579, in _apply module._apply(fn) File "/home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 579, in _apply module._apply(fn) File "/home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 579, in _apply module._apply(fn) File "/home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 602, in _apply param_applied = fn(param) File "/home/admin/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 925, in convert return t.to(device, dtype if t.is_floating_point() or t.is_complex() else None, non_blocking) [1189321094] map_info['map_portfolio_photo'] : {} final : True mtd_id 4573 list_pids : [1189321094] begin to insert list_values into mtr_datou_result : length of list_values in save_final : 1 insert ignore into MTRPhoto.mtr_datou_result (mtd_id, mtr_portfolio_id,mtr_photo_id,result,result_long,result_double,hashtag_id,proba, mtr_current_id) values (%s,%s,%s,%s,%s,%s,%s,%s,%s) on duplicate key update mtr_portfolio_id = mtr_portfolio_id list_values : [('4573', None, '1189321094', "[>, , , , , 'CUDA error: out of memory\\nCUDA kernel errors might be asynchronously reported at some other API call,so the stacktrace below might be incorrect.\\nFor debugging consider passing CUDA_LAUNCH_BLOCKING=1.']", '-1', '-1.0', '501120777', '1.0', None)] time used for this insertion : 0.01561737060546875 save_final ERROR in last step sam, CUDA error: out of memory CUDA kernel errors might be asynchronously reported at some other API call,so the stacktrace below might be incorrect. For debugging consider passing CUDA_LAUNCH_BLOCKING=1. time spend for datou_step_exec : 5.02626371383667 time spend to save output : 0.01684713363647461 total time spend for step 0 : 5.0431108474731445 need to delete datou_research and reload, so keep current state 1 need to delete datou_research and reload, so keep current state 1 caffe_path_current : About to save ! 2 After save, about to update current ! datou_cur_ids : [] len(datou.list_steps) : 1 output : None ERROR nb objects espect : 98 nb_objects detect : 0 ERROR sam FAILED ############################### TEST frcnn ################################ test frcnn Inside batchDatouExec : verbose : True ##### chargement datou SELECT name, created_at,limit_max FROM MTRDatou.mtr_datou WHERE id=4184 SELECT mtd.id, mtdt.`type`, mtd.`param`, mtd.param_json, mtdt.nb_input, mtdt.nb_output, mtdt.prod, mtdt.is_local, mtdt.is_datou_depend, mtdt.is_photo_id_local FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_step_types mtdt WHERE mtdt.`id`=mtd.`type` AND mtd.mtd_id=4184 SELECT mtd.id, mtd.mtd_id, mdsdt.id, mdsdt.name, mdsdt.description, msid.output_or_input, msid.data_order_id, mdsdt.type FROM MTRDatou.mtr_datou_step mtd, MTRDatou.mtr_datou_steptype_io_datatypes msid, MTRDatou.mtr_datou_step_data_types mdsdt WHERE mtd.`type`=msid.`mtr_datou_step_type` AND mtd.mtd_id= 4184 AND msid.data_type=mdsdt.id SELECT mts_id_output, id_output, mts_id_input, id_input FROM MTRDatou.mtr_datou_step_by_step WHERE mtd_id=4184 # VR 17-11-17 : to create in DB ! Here we check the datou graph and we reorder steps ! Tree builded and cycle checked, now we need to re-order the steps ! We have currenlty an error because there is no dependence between the last step for the case tile - detect - glue We can either keep the depence of, it is better to keep an order compatible with the id of steps if we do not have sons, so a lexical order : (number_son, step_id) DONE and to test : checkNoCycle ! We are managing only one step so we do not consider checkConsistencyNbInputNbOutput ! We are managing only one step so we do not consider checkConsistencyTypeOutputInput ! no param json to modify List Step Type Loaded in datou : frcnn list_input_json : [] ##### fin chargement datou ##### chargement data ##### Call load_data_input : nb_thread : 5 origin SELECT photo_id, url FROM MTRBack.photos ph WHERE photo_id IN (917754606) Found this number of photos: 1 ##### Call download_photos : nb_thread : 5 begin to download photo : 917754606 download finish for photo 917754606 we have missing 0 photos in the step downloads : photo missing : [] try to delete the photos missing in DB ##### After download_photos length of list_filenames : 1 ; length of list_pids : 1 ; length of list_args : 1 ##### After load_data_input time to download the photos : 0.10099124908447266 #### fin chargement data Blocking on flush ? No conitnuing About to test input to load we should then remove the video here, and this would fix the bug of datou_current ! Calling datou_exec Inside datou_exec : verbose : True number of steps : 1 step1:frcnn Tue Jul 15 06:36:42 2025 VR 17-11-17 : now, only for linear exec dependencies tree, some output goes to fill the input of the next VR 22-3-18 : now we test the dependencies tree, but keep two separate code for datou_prepare_output_input until the code is correctly tested, clean and works in both case VR 22-3-18 : but we use the first code for the first step id = -1, build in the code of datou_exec VR 22-3-18 : we should manage here the case when we are at the first step instead of building this step before datou_exec After prepare type args : Here we display some param of map_info ! map_filenames : {'temp/1752554202_118993_917754606_35f3c9ae49686a6be16030c6ec25c9ee.jpg': 917754606} map_photo_id_path_extension : {917754606: {'path': 'temp/1752554202_118993_917754606_35f3c9ae49686a6be16030c6ec25c9ee.jpg', 'extension': 'jpg'}} map_subphoto_mainphoto : {} Beginning of datou step Faster rcnn ! classes : ['background', 'plaque'] pht : 4370 caffemodel_name (should be vgg16_immat_307 but not used because net loaded outside in the fonction) : {'id': 3375, 'mtr_user_id': 31, 'name': 'detection_plaque_valcor_010622', 'pb_hashtag_id': 0, 'live': b'\x00', 'list_hashtags': 'background,plaque', 'svm_portfolios_learning': '0,0', 'photo_hashtag_type': 4370, 'photo_desc_type': 5676, 'type_classification': 'caffe_faster_rcnn', 'hashtag_id_list': '0,0'} To loadFromThcl() model_param file didn't exist model_name : detection_plaque_valcor_010622 model_type : caffe_faster_rcnn list file need : ['caffemodel', 'test.prototxt'] file exist in s3 : ['caffemodel', 'test.prototxt'] file manque in s3 : [] WARNING: Logging before InitGoogleLogging() is written to STDERR E0715 06:36:44.065357 118993 common.cpp:114] Cannot create Cublas handle. Cublas won't be available. E0715 06:36:44.071583 118993 common.cpp:121] Cannot create Curand generator. Curand won't be available. F0715 06:36:44.081550 118993 syncedmem.hpp:22] Check failed: error == cudaSuccess (2 vs. 0) out of memory *** Check failure stack trace: *** Command terminated by signal 6 5.99user 6.92system 1:18.73elapsed 16%CPU (0avgtext+0avgdata 1308900maxresident)k 151344inputs+3344outputs (1115major+571821minor)pagefaults 0swaps